Software Alternatives & Reviews

datagran VS Ploomber

Compare datagran VS Ploomber and see what are their differences

datagran logo datagran

All-in-one AI data workspace

Ploomber logo Ploomber

Ploomber is an open-source framework that helps data scientists quickly deploy the code they develop in interactive environments (Jupyter, VScode, PyCharm, etc.), eliminating the need for time-consuming manual porting to production platforms.
  • datagran Landing page
    Landing page //
    2023-10-22
  • Ploomber Landing page
    Landing page //
    2023-08-24

datagran videos

Datagran Review on AppSumo

Ploomber videos

Open-Source Spotlight - Ploomber - Eduardo Blancas

More videos:

  • Review - EDUARDO BLANCAS - Ploomber: Open-Source Tools for Maintainable and Production-Ready Data Science
  • Review - Ploomber: Developing Maintainable & Reproducible Data- Eduardo Blancas, Ido Michael | SciPy 2022

Category Popularity

0-100% (relative to datagran and Ploomber)
AI
58 58%
42% 42
Developer Tools
51 51%
49% 49
No Code
52 52%
48% 48
SaaS
100 100%
0% 0

User comments

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Social recommendations and mentions

Based on our record, Ploomber seems to be more popular. It has been mentiond 7 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

datagran mentions (0)

We have not tracked any mentions of datagran yet. Tracking of datagran recommendations started around Mar 2021.

Ploomber mentions (7)

  • Show HN: JupySQL – a SQL client for Jupyter (ipython-SQL successor)
    - One-click sharing powered by Ploomber Cloud: https://ploomber.io Note that JupySQL is a fork of ipython-sql; which is no longer actively developed. Catherine, ipython-sql's creator, was kind enough to pass the project to us (check out ipython-sql's README). We'd love to learn what you think and what features we can ship for JupySQL to be the best SQL client! Please let us know in the comments! - Source: Hacker News / 5 months ago
  • A three-part series on deploying a Data Science Platform on AWS
    Developing end-to-end data science infrastructure can get complex. For example, many of us might have struggled to try to integrate AWS services and deal with configuration, permissions, etc. At Ploomber, we’ve worked with many companies in a wide range of industries, such as energy, entertainment, computational chemistry, and genomics, so we are constantly looking for simple solutions to get them started with... Source: over 1 year ago
  • Is Colab still the place to go?
    If you like working locally with notebooks, you can run via the free tier of ploomber, that'll allow you to get the Ram/Compute you need for the bigger models as part of the free tier. Also, it has the historical executions so you don't need to remember what you executed an hour later! Source: over 1 year ago
  • Saving log files
    That's what we do for lineage with https://ploomber.io/. Source: over 1 year ago
  • Three Tools for Executing Jupyter Notebooks
    NBClient supports running notebooks via CLI for the most basic use cases. However, for more sophisticated execution options, consider the Ploomber! - Source: dev.to / almost 2 years ago
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What are some alternatives?

When comparing datagran and Ploomber, you can also consider the following products

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Spacelift.io - Collaborative Infrastructure For Modern Software Teams

ZenML - Create reproducible machine learning pipelines